In this project, we will develop novel quantitative high-throughput (HT) metabolic profiling methods and workflows that will facilitate the study and understanding of the dynamics of some of the building blocks of life (namely; metabolites, enzymes and cells), their interactions, and how their functioning is modulated by their environment. These novel HT workflows can be applied for a range of fields in the life sciences such as the characterization of enzyme activity, cell-based screening, drug research and future health care.

Using available knowledge about the kinetics in combination with historical data, a network-model based on ordinary differential equations (ODEs) will be built of all relevant chemical components and their dependence on the enzymes to be tested. This model will serve several goals. First, the model will be used on-line as a basis for simultaneous on-the fly estimation of relevant kinetic constants based on all measured progress curves; possibly the model has to be reduced to gain speed in solving the ODEs. This should also entail on-the-fly assessment of the quality of the estimates of the kinetic constants thereby possibly ending the experiment once a pre-set quality has been reached. Secondly, the model will be used to simulate and test different scenarios, should the measurement be done fast and less precise or slower and more precise? How many time-points are needed to obtain a pre-set quality of the estimated kinetics constants? Thirdly, the model will be used in increasingly complex mixtures and matrices to infer its robustness. This may call for adaptations of the model, e.g., simplifications which makes the model less vulnerable to the specifics of the matrices. Fourthly, relationships between model parameters and quality performance of the enzymes in applications will be established by well-chosen experiments of increasing complexity. Finally, the model will be used to find optimal mixtures of enzymes or substrates for the fermentation studied.

What are you going to do

You are expected to:

• build computational ODE models for enzymatic reaction networks;
• report and present your work on a regular basis to our industrial and academic partners;
• work closely together with analytical chemists;
• develop optimal measurement schemes for high throughput experiments;
• actively participate in scientific discussions in our research group.

What do we require

• A PhD degree in the field of chemometrics, systems biology, applied mathematics or computational science.
• One or more publications as first author in a peer-reviewed scientific journal.
• Preferentially, skilled in data analysis and building models from data.
• Experience with computational optimalization techniques.
• An ambitious person that is a team player with an open character.
• An appreciation to contribute to valorization efforts and to foster collaborations with academic and industrial partners.
• an understanding and acceptance of the sensitivity of confidentiality in public-private collaborations.

Our offer

A temporary contract for 30,4-38 hours a week, preferably starting on 1 March 2022, for the duration of six months. An extension for 18 months subsequently follows if we assess your performance positive.      

The salary, depending on relevant work experience before the beginning of the employment contract, will be between €2,836 to €4,474 (scale 10) gross per month, based on a fulltime contract (38 hours a week). This is exclusive 8% holiday allowance and 8.3% end-of-year bonus. A favourable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants. The Collective Labour Agreement of Dutch Universities is applicable.

Are you curious about our extensive package of secondary employment benefits like our excellent opportunities for study and development? Take a look here.

University of Amsterdam

With over 6,000 employees, 30,000 students and a budget of more than 600 million euros, the University of Amsterdam (UvA) is an intellectual hub within the Netherlands. Teaching and research at the UvA are conducted within seven faculties: Humanities, Social and Behavioural Sciences, Economics and Business, Law, Science, Medicine and Dentistry. Housed on four city campuses in or near the heart of Amsterdam, where disciplines come together and interact, the faculties have close links with thousands of researchers and hundreds of institutions at home and abroad.  

The UvA’s students and employees are independent thinkers, competent rebels who dare to question dogmas and aren’t satisfied with easy answers and standard solutions. To work at the UvA is to work in an independent, creative, innovative and international climate characterised by an open atmosphere and a genuine engagement with the city of Amsterdam and society.

Faculty of Science - Institute for Life Sciences

The Faculty of Science has a student body of around 7,000, as well as 1,600 members of staff working in education, research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works, be it elementary particles, the birth of the universe or the functioning of the brain.

The Swammerdam Institute for Life Sciences (SILS) is one of the Faculty of Science’s largest institutes. Its approximately 240 scientists and staff members work in 16 research groups that perform excellent research centred on three themes: 1) Cell & Sytems Biology, 2) Neurosciences, and 3) Molecular Life Sciences.

This postdoc position is within Biosystems Data Analysis group and in close cooperation with partners from academia and industry. The Biosystems Data Analysis group develops and implements models, advanced statistical and machine learning tools